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Application-based big data development framework for health sciences libraries.

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Summary
This summary is machine-generated.

This study introduces a performance-based evaluation framework for big data analytics (BDA) in health sciences libraries. It highlights the need for skilled professionals to enhance library services and data analysis capabilities.

Keywords:
competenciesinformation and communication technologies (ICTs)libraries, health science

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Area of Science:

  • Health Informatics
  • Library Science
  • Data Science

Background:

  • The increasing volume of data in health sciences necessitates effective evaluation of big data analytics (BDA) applications within libraries.
  • Existing frameworks may not adequately address the unique challenges and opportunities of BDA in digital health environments.
  • Performance-based evaluation is crucial for optimizing library services and demonstrating value in health institutes.

Purpose of the Study:

  • To present a theoretical framework for a performance-based evaluation system for health sciences libraries utilizing big data analytics.
  • To develop an application-based big data development framework tailored for health sciences libraries.
  • To propose a model for measuring an organization's capacity for data analysis in health libraries.

Main Methods:

  • A comprehensive literature review was conducted on big data analytics, diffusion of innovation theory, and the technology acceptance model.
  • A systematic evaluation approach was developed, focusing on five key components of BDA: data culture, organizational infrastructure, responsibilities, skills, and technology competence.
  • The study integrates BDA into health sciences libraries for service and performance improvement.

Main Results:

  • The study identified the critical components for evaluating BDA in health sciences libraries.
  • A theoretical framework and an application-based model for BDA integration were proposed.
  • The necessity for professionals with both technical and professional expertise in BDA was emphasized.

Conclusions:

  • The proposed model can measure an organization's ability to analyze vast data, validating the association between big data analysis and practices in health libraries.
  • Implementing this framework can lead to improved library services and performance through effective BDA.
  • There is a clear need for skilled professionals to drive successful BDA initiatives in health sciences libraries.